题目：Level of aggregation and magnitude of energy rebound: China’s industrial sector
主讲人：Baiding Hu 博士（Faculty of Agribusiness and Commerce at Lincoln University, 新西兰）
时间：2015年5月4日上午9：00-11：00
地点：主楼6楼（能源与环境政策研究中心）
主讲人介绍：
     Dr Baiding Hu is a senior lecturer of economics in the Faculty of Agribusiness and Commerce at Lincoln University, Christchurch, New Zealand. He holds a PhD in economics from the University of Western Australia. Prior to joining Lincoln University, he had held faculty positions at La Trobe and Macquarie Universities in Australia. Baiding has also been an economist for the National Institute of Economics and Industry Research, a Melbourne based private consulting firm, where he was involved in providing forecasts of sect oral energy consumption for both the public and private sectors. His current research interests include energy economics, productivity and efficiency, and Chinese economy.
内容介绍：
    The research starts by examining input factors’ growth in the sector over the period 1990-2012, which shows that while the consumption of coal is slowing down in a relative sense, that of electricity is picking up. Since total factor productivity is likely to be driven by improving energy quality, the aforementioned increasing electrification serves as the pretext for investigation of rebound effects in the sector. The research then proceeds to estimate total factor productivity growth for the sector using sectoral level (aggregated) data, followed by a decomposition analysis to assess rebound effect. Because of the availability of subsectoral data, the information on the inter-subsectoral linkages is explored in view of the business cycle literature. This is to recognize that different subsectors are subject to different technological shocks and different compositions of energy consumption. These differences will not necessarily averaged out as implied in the aggregate data. Thus, two sets of rebound effect estimates are produced for the sector, one obtained from the aggregated data and the other from the disaggregated (subsect oral) data. The research concludes by arguing why the rebound estimate based on the disaggregated data is more reasonable on the one hand, and outlining cases whereby the level of aggregation does not matter on the other.

（主办：能源与环境政策研究中心）